https://threedle.github.io/text2mesh/

3D mesh stylization driven by a text input in PyTorch
https://threedle.github.io/text2mesh/

3d computer-graphics differentiable-rendering geometry-processing mesh-generation meshes neural-fields neural-style pytorch

Last synced: 9 days ago
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3D mesh stylization driven by a text input in PyTorch

• Host: GitHub
• URL: https://threedle.github.io/text2mesh/
• Owner: threedle
• License: mit
• Created: 2021-11-20T21:17:52.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2024-05-19T16:19:52.000Z (6 months ago)
• Last Synced: 2024-10-28T02:18:12.903Z (14 days ago)
• Topics: 3d, computer-graphics, differentiable-rendering, geometry-processing, mesh-generation, meshes, neural-fields, neural-style, pytorch
• Language: Jupyter Notebook
• Homepage: https://threedle.github.io/text2mesh/
• Size: 1.88 GB
• Stars: 923
• Watchers: 22
• Forks: 127
• Open Issues: 21
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Text2Mesh [[Project Page](https://threedle.github.io/text2mesh/)]

[![arXiv](https://img.shields.io/badge/arXiv-Text2Mesh-b31b1b.svg)](https://arxiv.org/abs/2112.03221)

![Pytorch](https://img.shields.io/badge/PyTorch->=1.9.0-Red?logo=pytorch)

![crochet candle](images/vases.gif)

**Text2Mesh** is a method for text-driven stylization of a 3D mesh, as described in "Text2Mesh: Text-Driven Neural Stylization for Meshes" CVPR 2022.

## Getting Started

### Installation

**Note:** The below installation will fail if run on something other than a CUDA GPU machine.

```

conda env create --file text2mesh.yml

conda activate text2mesh

```

If you experience an error installing kaolin saying something like `nvcc not found`, you may need to set your `CUDA_HOME` environment variable to the 11.3 folder i.e. `export CUDA_HOME=/usr/local/cuda-11.3`, then rerunning the installation. 

### System Requirements

- Python 3.7

- CUDA 11

- GPU w/ minimum 8 GB ram

### Run examples

Call the below shell scripts to generate example styles. 

```bash

# cobblestone alien

./demo/run_alien_cobble.sh

# shoe made of cactus 

./demo/run_shoe.sh

# lamp made of brick

./demo/run_lamp.sh

# ...

```

The outputs will be saved to `results/demo`, with the stylized .obj files, colored and uncolored render views, and screenshots during training.

#### Outputs

















































































## Important tips for running on your own meshes

Text2Mesh learns to produce color and displacements over the input mesh vertices. The mesh triangulation effectively defines the resolution for the stylization. Therefore, it is important that the mesh triangles are small enough such that they can accurately potray the color and displacement. If a mesh contains large triangles, the stylization will not contain sufficent resolution (and leads to low quality results). For example, the triangles on the seat of the chair below are too large.







You should remesh such shapes as a pre-process in to create smaller triangles which are uniformly dispersed over the surface. Our example remeshing script can be used with the following command (and then use the remeshed shape with Text2Mesh):

```

python3 remesh.py --obj_path [the mesh's path] --output_path [the full output path]

```

For example, to remesh a file name called `chair.obj`, the following command should be run:  

```

python3 remesh.py --obj_path chair.obj --output_path chair-remesh.obj

```

## Other implementations

[Kaggle Notebook](https://www.kaggle.com/neverix/text2mesh/) (by [neverix](https://www.kaggle.com/neverix))

## External projects using Text2Mesh

- [Endava 3D Asset Tool](https://www.endava.com/en/blog/Engineering/2022/An-R-D-Project-on-AI-in-3D-Asset-Creation-for-Games) integrates Text2Mesh into their modeling software to create 3D assets for games.

- [Psychedelic Trips Art Gallery](https://www.flickr.com/photos/mcanet/sets/72177720299890759/) uses Text2Mesh to generate AI Art and fabricate (3D print) the results.

## Citation

```

@InProceedings{Michel_2022_CVPR,

    author    = {Michel, Oscar and Bar-On, Roi and Liu, Richard and Benaim, Sagie and Hanocka, Rana},

    title     = {Text2Mesh: Text-Driven Neural Stylization for Meshes},

    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},

    month     = {June},

    year      = {2022},

    pages     = {13492-13502}

}

```